Modern motor vehicles often include one or more in-vehicle information systems that provide a wide variety of information and entertainment options to occupants in the vehicle. Common services that are provided by the in-vehicle information systems include, but are not limited to, vehicle state and diagnostic information, navigation applications, hands-free telephony, radio and music playback, and traffic condition alerts. In-vehicle information systems often include multiple input and output devices. For example, traditional buttons and control knobs that are used to operate radios and audio systems are commonly used in vehicle information systems. More recent forms of vehicle input include touchscreen input devices that combine input and display into a single screen, as well as voice-activated functions where the in-vehicle information system responds to voice commands. Examples of output systems include mechanical instrument gauges, output display panels, such as liquid crystal display (LCD) panels, and audio output devices that produce synthesized speech.
User interfaces for an in-vehicle information system need to enable the user to obtain the information being sought without undue distraction. While most such information systems use control knobs or touch screens with displays for user interaction, some systems incorporate multiple modalities, such as speech and gesture recognition. In these systems that use multiple modalities, gesture input plays a key role. One challenge for in-vehicle hand gesture recognition arises from the diversity of possible hand gestures. Some of this diversity occurs because a driver's focus is on vehicle operation rather than on performing a gesture. Consequently, hand gestures are noisy and may include meaningless components, such as making a long starting stroke before actually performing the gesture. Including such noisy strokes in the gesture can lead to misidentification of a gesture. Another contributing factor to gesture diversity is the variation in illumination conditions in a vehicle. Most generic gesture recognition systems are built for in-door environments. Different color space representations, skin regions versus non-skin regions classification rules, automatic white balance calibration, or depth information are often used to filter the cluttered environmental conditions. Because in-vehicle environments differ from one another so drastically, these software tools are not reliably successful in identifying hand gestures. Consequently, improvements in the ability of in-vehicle information systems to recognize hand gestures are worthwhile.